We propose a novel factor model for option returns. Option exposures are estimated nonparametrically, and factor risk premia can vary nonlinearly with states. The model is estimated using regressions with minimal assumptions on factor and option return dynamics. We estimate the model using index options to characterize the conditional risk premia for factors of interest, such as the market return, market variance, tail and intermediary risk factors, higher moments, and the VIX term structure slope. Together, market return and variance explain more than 90% of option return variation. Unconditionally, the magnitude of the variance risk premium is plausible. It displays pronounced time variation, spikes during crises, and always has the expected sign.

中文翻译：

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对指数期权收益隐含的条件因子风险溢价进行建模

我们提出了一种新颖的期权收益因子模型。期权风险是非参数估计的，因子风险溢价可能随状态呈非线性变化。该模型是使用对因子和期权收益动态的最小假设的回归来估计的。我们使用指数期权来估计模型，以表征感兴趣因素的条件风险溢价，例如市场回报、市场方差、尾部和中间风险因素、高矩以及 VIX 期限结构斜率。市场回报和方差共同解释了 90% 以上的期权回报变化。无条件地，方差风险溢价的大小是合理的。它显示出明显的时间变化、危机期间的峰值，并且始终具有预期的迹象。